Homework 1

Author

Jack Stephens

Published

September 4, 2024

Load Packages

library(Hmisc)
library(tidyverse)

Problem 1

Survey

September 4, 2024 - 1:51PM

Campuswire

Problem 2

Question 1

Common people in England and Wales.

Question 2

The sampling strategy of this study is random sampling because the survey ensures that every household within the target population has an equal chance of being selected.

Question 3

The 38,000 people surveyed and the residents of the neighborhoods on the record at the police station

Question 4

The target population of these data sets are the police departments in England and Wales to see which areas in their country has the most experience with crime.

Question 5

The reliability of this data set is not great solely because there are enough variables taken into account. When only surveying 38,000 of about 66.97 million people, many accounts can be different or non-reliable. In data set 2 it could be better because the stations can see where they have been the most and plan accordingly. This would cause the validity of set 2 to also be better than set 1. Finally, I would say that set 2 is a more effective method, but set 1 is more generalizable to the target population.

Problem 3

Question 1

The <- notation is equivalent to an = sign in R and is often used to declare variables. After running this code chunk, the named dataframe df appears in the environment on the right-hand side of RStudio.

df <- read_csv('https://www.openintro.org/data/csv/babies.csv')
Rows: 1236 Columns: 8
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (8): case, bwt, gestation, parity, age, height, weight, smoke

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

Question 2

The notation Hmisc:: directly calls this function from the Hmisc package. describe() is a common function name, and sometimes this is needed to indicate to R which function from which package you want to use. The pipe feature |> sends the results of the first line directly into the function on the 2nd line and is a convenient way to chain functions together.

This code prints a useful and attractive summary of the data set we are using.

Hmisc::describe(df) |> 
  html()
df Descriptives
df

8 Variables   1236 Observations
case
image
        n  missing distinct     Info     Mean      Gmd      .05      .10      .25 
     1236        0     1236        1    618.5    412.3    62.75   124.50   309.75 
      .50      .75      .90      .95 
   618.50   927.25  1112.50  1174.25
lowest : 1 2 3 4 5 , highest: 1232 1233 1234 1235 1236
bwt
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
123601071119.620.33 88.0 97.0108.8120.0131.0142.0149.0
lowest : 55 58 62 63 65 , highest: 169 170 173 174 176
gestation
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
1223131060.999279.316.57252.0262.0272.0280.0288.0295.8302.0
lowest : 148 181 204 223 224 , highest: 330 336 338 351 353
parity
nmissingdistinctInfoSumMeanGmd
1236020.573150.25490.3801
age
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
12342300.99727.266.50619202326313638
lowest : 15 17 18 19 20 , highest: 41 42 43 44 45
height
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
121422190.98664.052.83960616264666768
 Value         53    54    56    57    58    59    60    61    62    63    64    65
 Frequency      1     1     1     1    10    26    55   105   131   166   183   182
 Proportion 0.001 0.001 0.001 0.001 0.008 0.021 0.045 0.086 0.108 0.137 0.151 0.150
                                                     
 Value         66    67    68    69    70    71    72
 Frequency    153   105    54    20    13     6     1
 Proportion 0.126 0.086 0.044 0.016 0.011 0.005 0.001
For the frequency table, variable is rounded to the nearest 0
weight
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
1200361050.999128.622.39102.0105.0114.8125.0139.0155.0170.0
lowest : 87 89 90 91 92 , highest: 215 217 220 228 250
smoke
nmissingdistinctInfoSumMeanGmd
12261020.7174840.39480.4782

Question 3

The Child Health and Development Studies investigate a range of topics. One study, in particular, considered all pregnancies between 1960 and 1967 among women in the Kaiser Foundation Health Plan in the San Francisco East Bay area. The variables in this data set are as follows.

Data Dictionary
Variable Name Variable Description Variable Type
case id number Categorical - Ordinal
bwt birthweight, in ounces Numerical - Continiuous
gestation length of gestation, in days Numerical- Discrete
parity binary indicator for a first pregnancy (0 = first pregnancy) Categorical - Nominal
age mother’s age in years Numerical - Continuous
height mother’s height in inches Numerical - Discrete
weight mother’s weight in pounds Numerical - Continuous
smoke binary indicator for whether the mother smokes numerical

Question 4

Below, 2 numeric variables were investigated for potential relationships. The independent, explanatory variable I chose is variable_name, and the dependent, response variable I chose is variable_name.

df |>
  ggplot(aes(x = weight, # please change these
              y = age)) + 
  geom_point()
Warning: Removed 37 rows containing missing values or values outside the scale range
(`geom_point()`).

The weight stays pretty consistent throughout the ages. The mothers weight for the most part stays within 100-150 pounds all the way from 15, 16 years old to 44, 45.

Session Info

This portion of the document describes the conditions in RStudio under which this report was created. This is important to include so that work is reproducible by others.

xfun::session_info()
R version 4.4.1 (2024-06-14)
Platform: aarch64-apple-darwin20
Running under: macOS Ventura 13.5

Locale: en_US.UTF-8 / en_US.UTF-8 / en_US.UTF-8 / C / en_US.UTF-8 / en_US.UTF-8

Package version:
  askpass_1.2.0       backports_1.5.0     base64enc_0.1-3    
  bit_4.0.5           bit64_4.0.5         blob_1.2.4         
  broom_1.0.6         bslib_0.8.0         cachem_1.1.0       
  callr_3.7.6         cellranger_1.1.0    checkmate_2.3.2    
  cli_3.6.3           clipr_0.8.0         cluster_2.1.6      
  colorspace_2.1-1    compiler_4.4.1      conflicted_1.2.0   
  cpp11_0.4.7         crayon_1.5.3        curl_5.2.1         
  data.table_1.15.4   DBI_1.2.3           dbplyr_2.5.0       
  digest_0.6.37       dplyr_1.1.4         dtplyr_1.3.1       
  evaluate_0.24.0     fansi_1.0.6         farver_2.1.2       
  fastmap_1.2.0       fontawesome_0.5.2   forcats_1.0.0      
  foreign_0.8-86      Formula_1.2-5       fs_1.6.4           
  gargle_1.5.2        generics_0.1.3      ggplot2_3.5.1      
  glue_1.7.0          googledrive_2.1.1   googlesheets4_1.1.1
  graphics_4.4.1      grDevices_4.4.1     grid_4.4.1         
  gridExtra_2.3       gtable_0.3.5        haven_2.5.4        
  highr_0.11          Hmisc_5.1-3         hms_1.1.3          
  htmlTable_2.4.3     htmltools_0.5.8.1   htmlwidgets_1.6.4  
  httr_1.4.7          ids_1.0.1           isoband_0.2.7      
  jquerylib_0.1.4     jsonlite_1.8.8      knitr_1.48         
  labeling_0.4.3      lattice_0.22.6      lifecycle_1.0.4    
  lubridate_1.9.3     magrittr_2.0.3      MASS_7.3.60.2      
  Matrix_1.7.0        memoise_2.0.1       methods_4.4.1      
  mgcv_1.9.1          mime_0.12           modelr_0.1.11      
  munsell_0.5.1       nlme_3.1.164        nnet_7.3-19        
  openssl_2.2.1       parallel_4.4.1      pillar_1.9.0       
  pkgconfig_2.0.3     prettyunits_1.2.0   processx_3.8.4     
  progress_1.2.3      ps_1.7.7            purrr_1.0.2        
  R6_2.5.1            ragg_1.3.2          rappdirs_0.3.3     
  RColorBrewer_1.1.3  readr_2.1.5         readxl_1.4.3       
  rematch_2.0.0       rematch2_2.1.2      reprex_2.1.1       
  rlang_1.1.4         rmarkdown_2.28      rpart_4.1.23       
  rstudioapi_0.16.0   rvest_1.0.4         sass_0.4.9         
  scales_1.3.0        selectr_0.4.2       splines_4.4.1      
  stats_4.4.1         stringi_1.8.4       stringr_1.5.1      
  sys_3.4.2           systemfonts_1.1.0   textshaping_0.4.0  
  tibble_3.2.1        tidyr_1.3.1         tidyselect_1.2.1   
  tidyverse_2.0.0     timechange_0.3.0    tinytex_0.52       
  tools_4.4.1         tzdb_0.4.0          utf8_1.2.4         
  utils_4.4.1         uuid_1.2.1          vctrs_0.6.5        
  viridis_0.6.5       viridisLite_0.4.2   vroom_1.6.5        
  withr_3.0.1         xfun_0.47           xml2_1.3.6         
  yaml_2.3.10